This invention relates to a system and method for collecting computer network traffic, particularly Internet traffic, in a manner that does not associate personally identifiable information with network usage data, and creating online behavior profiles that are unassociated with individual users. Specifically, the system and method of the invention will permit Internet service providers (ISP) and online merchants to monitor transactions made over a secure or encrypted link such as the Secure Socket Layer (SSL), and to create behavior profiles without violating customer confidentiality.
The Internet has rapidly grown into a center for conducting commerce with unprecedented efficiency and commercial advantage; however, the Internet also presents numerous new challenges to the development and execution of appropriate business models and processes. To design and implement effective marketing and business plans, companies need to gain a better understanding of consumer behavior and preferences while they are conducting Internet commerce.
In the current Internet world, it has become desirable for service providers and merchants to obtain specific information about Internet users for the purpose of improving the marketing of products and services, and tailoring products and services to meet the requirements of specific customer types. In order to obtain the most effective data, it is desirable to aggregate usage data from companies that provide Internet access to their employees, and from ISPs that provide access to subscribers.
However, the collection of Internet transaction data raises many concerns about consumer confidentiality and privacy. First, participating companies and ISPs desire to maintain the confidentiality of their business information such as the number of subscribers, the geographical locations of each subscriber, and general usage data.
Additionally, many users are averse to having their actions monitored and tracked. Security concerns about the Internet have prevented many users from completing online transactions. Other users have completely stayed away from the Internet because of fears that their private information might become available to third parties in an uncontrolled manner.
Therefore, it is desirable to obtain detailed information about the behavior of users while ensuring subscriber, employee, and company privacy.
Today, there are several major approaches to collecting Internet transaction data. The first is through traditional polling techniques. In this method, user behavior profiles are developed from users' answers to questionnaires regarding their Internet use. Unfortunately, this technique suffers from bias and fails to provide the detail that marketers need.
The next approach to collecting network transaction data is by using logfiles generated by network devices such as Web servers and proxies. Logfiles provide increased detail and accuracy compared to polling techniques; however, they fail to protect user privacy and confidentiality. Logfiles generally contain a username or an Internet Protocol (IP) address that can be used to tie behavior to a particular individual. Additionally, Web server logfiles alone are ineffective in characterizing user behavior because they only contain the cross-section Internet traffic going to that Web server; the Web server logfiles are unable to accurately capture the behavior of a consumer who accesses multiple Web sites to assist in making purchasing decisions.
The last general approach to collecting network transaction data involves the use of unique identifiers called “cookies” inserted into an Internet browser. When the user accesses a Web site on the Internet, the Web server can read the inserted cookie to obtain the unique identifier and then store details about the current transaction associated with the unique identifier. This method fails to capture Internet usage for users that have cookies disabled on their browsers and also fails to capture Internet usage on Web sites that do not participate in capturing and aggregating usage data. Since the captured data is not complete, any behavior profile created using the data cannot be representative of Internet usage in the aggregate.
In building accurate user profiles, it is desirable to know the behavior and actions that lead up to a purchase. For example, it would be desirable to know that many users searched one online merchant site for books to purchase and then went to a different online merchant site to make the actual purchase. Since most transactions made on the Internet employ some security mechanism, such as SSL, to protect sensitive customer information (e.g., credit card numbers, addresses, and purchase information), it can be difficult for a monitoring system to determine whether a purchase was made, much less determine what was purchased.
Under current Federal Communications Commission (FCC) regulations, companies may have to provide protection of customer proprietary network information. By monitoring and recording detailed network information about individuals using logfiles or cookies, companies may be in violation of these FCC regulations. To date, there has been no effective way of obtaining online customer behavior profiles to allow service providers and merchants to tailor products and services better without possibly violating government regulations.
It becomes desirable, therefore, to provide a method and system where such information can be obtained while still maintaining the confidentiality of the customer (e.g., by characterizing such data in such a manner that it is free of personally identifiable information).